Neuro-fuzzy ensemble approach for microarray cancer gene expression data analysis

Zhenyu Wang, Vasile Palade, Yong Xu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

52 Citations (Scopus)

Abstract

A Neuro-Fuzzy Ensemble model (NFE) is proposed in this paper for analysing the gene expression data from microarray experiments. The proposed approach was tested on three benchmark cancer gene expression data sets. Experimental results show that our NFE model can be used as an efficient computational tool for microarray data analysis. In addition, compared to some current most widely used approaches, Neuro-Fuzzy(NF)-based models not only supply good classification results, but their behavior can also be explained and interpreted in human understandable terms, which provides the researchers with a better understanding of the data.

Original languageEnglish
Title of host publicationProceedings of the 2006 International Symposium on Evolving Fuzzy Systems, EFS'06
PublisherIEEE
Pages241-246
Number of pages6
ISBN (Print)0780397193, 9780780397194
DOIs
Publication statusPublished - 30 Nov 2006
Externally publishedYes
Event2006 International Symposium on Evolving Fuzzy Systems, EFS'06 - Lake District, United Kingdom
Duration: 7 Sep 20069 Sep 2006

Conference

Conference2006 International Symposium on Evolving Fuzzy Systems, EFS'06
CountryUnited Kingdom
CityLake District
Period7/09/069/09/06

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Applied Mathematics
  • Theoretical Computer Science

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  • Cite this

    Wang, Z., Palade, V., & Xu, Y. (2006). Neuro-fuzzy ensemble approach for microarray cancer gene expression data analysis. In Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems, EFS'06 (pp. 241-246). [4016708] IEEE. https://doi.org/10.1109/ISEFS.2006.251144